Bacteria with increased mutation frequency and antibioticresistance are enriched in the commensal flora of patients with high antibiotic usage

Gustafsson, Ingegerd

doi:10.1093/jac/dkg427

Cited by 55 publications

(42 citation statements)

References 26 publications

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“…Regardless of pathogen dynamics, it is unlikely that antibiotic treatment can successfully clear colonization of the host due to the large numbers of organisms in the commensal flora. Antibiotic resistant bacteria are more likely enriched in the commensal flora of patients with high antibiotic usage [28].…”

Section: Resultsmentioning

confidence: 99%

“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections

Geli

Laxminarayan

Dunne³

et al. 2012

PLoS ONE

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Historically, antibiotic treatment guidelines have aimed to maximize treatment efficacy and minimize toxicity, but have not considered the evolution of antibiotic resistance. Optimizing the duration and dosing of treatment to minimize the duration of symptomatic infection and selection pressure for resistance simultaneously has the potential to extend the useful therapeutic life of these valuable life-saving drugs without compromising the interests of individual patients.Here, using mathematical models, we explore the theoretical basis for shorter durations of treatment courses, including a range of ecological dynamics of bacteria that cause infections or colonize hosts as commensals. We find that immunity is an important mediating factor in determining the need for long duration of treatment. When immunity to infection is expected, shorter durations that reduce the selection for resistance without interfering with successful clinical outcome are likely to be supported. Adjusting drug treatment strategies to account for the impact of the differences in the ecological niche occupied by commensal flora relative to invasive bacteria could be effective in delaying the spread of bacterial resistance.

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Section: Resultsmentioning

confidence: 99%

“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections

Geli

Laxminarayan

Dunne³

et al. 2012

PLoS ONE

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“…These vary from 10 −9 mutations per cell (clarithromycin and amoxicillin) [86] to 10 −6 mutations per cell [87]. Mutation rates will vary with species and strain [87,88], but trimethoprim + AZT induces mutation rates comparable to those induced by ciprofloxacin [86]. …”

Section: Discussionmentioning

confidence: 99%

High-throughput identification and rational design of synergistic small-molecule pairs for combating and bypassing antibiotic resistance

et al. 2017

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Antibiotic-resistant infections kill approximately 23,000 people and cost $20,000,000,000 each year in the United States alone despite the widespread use of small-molecule antimicrobial combination therapy. Antibiotic combinations typically have an additive effect: the efficacy of the combination matches the sum of the efficacies of each antibiotic when used alone. Small molecules can also act synergistically when the efficacy of the combination is greater than the additive efficacy. However, synergistic combinations are rare and have been historically difficult to identify. High-throughput identification of synergistic pairs is limited by the scale of potential combinations: a modest collection of 1,000 small molecules involves 1 million pairwise combinations. Here, we describe a high-throughput method for rapid identification of synergistic small-molecule pairs, the overlap2 method (O2M). O2M extracts patterns from chemical-genetic datasets, which are created when a collection of mutants is grown in the presence of hundreds of different small molecules, producing a precise set of phenotypes induced by each small molecule across the mutant set. The identification of mutants that show the same phenotype when treated with known synergistic molecules allows us to pinpoint additional molecule combinations that also act synergistically. As a proof of concept, we focus on combinations with the antibiotics trimethoprim and sulfamethizole, which had been standard treatment against urinary tract infections until widespread resistance decreased efficacy. Using O2M, we screened a library of 2,000 small molecules and identified several that synergize with the antibiotic trimethoprim and/or sulfamethizole. The most potent of these synergistic interactions is with the antiviral drug azidothymidine (AZT). We then demonstrate that understanding the molecular mechanism underlying small-molecule synergistic interactions allows the rational design of additional combinations that bypass drug resistance. Trimethoprim and sulfamethizole are both folate biosynthesis inhibitors. We find that this activity disrupts nucleotide homeostasis, which blocks DNA replication in the presence of AZT. Building on these data, we show that other small molecules that disrupt nucleotide homeostasis through other mechanisms (hydroxyurea and floxuridine) also act synergistically with AZT. These novel combinations inhibit the growth and virulence of trimethoprim-resistant clinical Escherichia coli and Klebsiella pneumoniae isolates, suggesting that they may be able to be rapidly advanced into clinical use. In sum, we present a generalizable method to screen for novel synergistic combinations, to identify particular mechanisms resulting in synergy, and to use the mechanistic knowledge to rationally design new combinations that bypass drug resistance.

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“…bystander selection, see above), and that the prevalence of resistance in the microflora increases with antibiotic consumption [49] and the duration of treatment [50]. This evidence suggests that use of aggressive chemotherapy with the aim of minimizing mutational inputs into target pathogen populations only makes sense as a resistance management strategy if…”

Section: Empirical Evidencementioning

confidence: 99%

The path of least resistance: aggressive or moderate treatment?

et al. 2014

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The evolution of resistance to antimicrobial chemotherapy is a major and growing cause of human mortality and morbidity. Comparatively little attention has been paid to how different patient treatment strategies shape the evolution of resistance. In particular, it is not clear whether treating individual patients aggressively with high drug dosages and long treatment durations, or moderately with low dosages and short durations can better prevent the evolution and spread of drug resistance. Here, we summarize the very limited available empirical evidence across different pathogens and provide a conceptual framework describing the information required to effectively manage drug pressure to minimize resistance evolution.

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Bacteria with increased mutation frequency and antibioticresistance are enriched in the commensal flora of patients with high antibiotic usage

Abstract: High antibiotic use selected for commensals with highly increased resistance and a slight increase in mutation frequency.

Cited by 55 publications

References 26 publications

“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections

“One-Size-Fits-All”? Optimizing Treatment Duration for Bacterial Infections

High-throughput identification and rational design of synergistic small-molecule pairs for combating and bypassing antibiotic resistance

The path of least resistance: aggressive or moderate treatment?

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